Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy

  • Marco Lippi
  • Andrea Passerini
  • Marco Punta
  • Paolo Frasconi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7524)


We present an application of machine learning algorithms for the identification of metalloproteins and metal binding sites on a genome scale. An extensive evaluation conducted in combination with X-ray absorption spectroscopy shows the great potentiality of the approach.


Metal Binding Metal Binding Site Wellcome Trust Sanger Institute Statistical Relational Learn SCO2 Protein 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Marco Lippi
    • 1
  • Andrea Passerini
    • 2
  • Marco Punta
    • 3
  • Paolo Frasconi
    • 4
  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversità di SienaItaly
  2. 2.Dipartimento di Ingegneria e Scienza dell’InformazioneUniversità di TrentoItaly
  3. 3.Wellcome Trust Sanger InstituteHinxtonUK
  4. 4.Dipartimento di Sistemi e InformaticaUniversità di FirenzeItaly

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